y. abbasi

The main objective of this study was to evaluate the surface and deep distribution of Pb, Ni and Cu in the wastewater-irrigated area of south of Tehran using GIS and Hydrus. It was expected to find a comprehensive information of heavy metals distribution and their accumulation in the soil. This study was carried out in wastewater-irrigated area of south of Tehran. Soil sampling from the top surface layer (0-15 cm) and wastewater channels was done. After sample analysis, ordinary Kriging method using different variogram in GIS was applied to explore the surface distribution of Ni, Pb and Cu heavy metals. Moreover, the deep percolation of heavy metals in the soil profile was simulated by Hydrus-1D in a duration of 210 days and the heavy metals concentrations in the soil were estimated. Exploration of the distribution of Pb using spherical model showed that the variation of this element was in the range of 20-70 mg/kg. This amount varied to 50-60 mg/kg for Cu and about 30 mg/kg for Ni. Moreover, the simulation of heavy metals deep percolation using Hydrus revealed that the most accumulation of heavy metals happened in the 0-15 cm soil surface layer and for deeper layer, this trend was descending. Comparing the concentration of Pb, Cu and Ni with the maximum allowable amounts of WHO standards demonstrated that Pb concentration was more than the threshold limit. Finally, the applied models could simulate soil’s heavy metals content for both surface and deep distribution in the studied area.

In this paper, the vision based formation control of a leader-follower aerial robotic system is discussed while communication failure between the robots is considered. Based on vision sensors and image processing computations, without any need to further communications, the follower robot obtains the line of sight angle and the corresponding distance from the leader. These information are used to calculate the leader speed and its path angle. Using model predictive control method, it is shown that even in the presence of communication failure between the robots, the flight formation can be controlled while the follower moves along the desired relative angle and keeps the corresponding distance. To this end, the control inputs are obtained in terms of normal and tangential acceleration of the follower. Simulation results show a good performance of the proposed model predictive controller in both ordinary, and communication failure conditions.